| Contributors | Affiliation | Role |
|---|---|---|
| Moran, Mary Ann | University of Georgia (UGA) | Principal Investigator |
| Copley, Nancy | Woods Hole Oceanographic Institution (WHOI BCO-DMO) | BCO-DMO Data Manager |
Incubation experiments examining concurrent changes in DOC composition and microbial transcription patterns were carried out in July 2014 (SIMCO1) and October 2014 (SIMCO2) at Sapelo Island, GA. This dataset contains the number of transcripts per liter of seawater for each taxon. Cells were collected by filtration at the time of initial surface water collection (Time 0) and after a 24 hr incubation (Time 24) for both high and low tide water collections on each of the two sample dates. Filters were processed for RNA extraction and mRNA-enriched material was sequenced on an Illumina HiSeq2500 run to produce single-end 250 bp reads.
Water samples were collected from Marsh Landing Dock on Sapelo Island GA, prefiltered through a 3 micron membrane filter to remove most eukaryotic microbes, and incubated in 10 L carboys in situ in the dark for 24 h. At the beginning and end of the incubation, three carboys were sacrificed for nucleic acid extraction on 0.2 micron membrane filters, and microbial transcripts were analyzed from two of the three replicates according to methods in Satinsky et al. 2013 and 2014 and protocols.io (https://www.protocols.io/g/moran-lab).
Reads were put through a quality control pipeline that removed rRNAs and internal standards added for quantification (Satinsky et al. 2013). Transcripts per liter of seawater at the beginning and end of the incubations were calculated based on internal standard recovery as described in Satinsky et al. 2013.
References:
Brandon M. Satinsky, Scott M. Gifford, Byron C. Crump, Mary Ann Moran, 2013. Chapter 12: "Use of Internal Standards for Quantitative Metatranscriptome and Metagenome Analysis" in Methods in Enzymology, Vol. 531. ISSN 0076-6879, http://dx.doi.org/10.1016/B978-0-12-407863-5.00012-5.
Brandon M. Satinskya, Byron C. Crumpb, Christa B. Smithc, Shalabh Sharmac, Brian L. Zielinskid, Mary Dohertye, Jun Mengc, Shulei Sunf, Patricia M. Medeirosc, John H. Pauld, Victoria J. Colese, Patricia L. Yagerc, and Mary Ann Moranc. 2014. Microspatial gene expression patterns in the Amazon River Plume. PNAS 111(30):11085-11090. www.pnas.org/cgi/doi/10.1073/pnas.1402782111
BCO-DMO Processing:
- added conventional header with dataset name, PI name, version date
- column names reformatted to comply with BCO-DMO standards
- replaced spaces with underscores
| File |
|---|
transcripts_per_L.csv (Comma Separated Values (.csv), 309 bytes) MD5:ebc622eba89e94b5a2ff595c2a5ea3fe Primary data file for dataset ID 661866 |
| Parameter | Description | Units |
| sample | sample identification: S1 = July 2014, S2 = October 2014, L versus H = low tide or high tide; 0 or 24 =time zero or time 24 h (at the time of sample collection or after 24 h incubation in the dark), and -1 or -2 = replicate designations. | unitless |
| transcripts_per_L | number of transcripts per liter | transcripts/liter |
| Dataset-specific Instrument Name | Illumina HiSeq2500 |
| Generic Instrument Name | Automated DNA Sequencer |
| Dataset-specific Description | mRNA-enriched material was sequenced |
| Generic Instrument Description | General term for a laboratory instrument used for deciphering the order of bases in a strand of DNA. Sanger sequencers detect fluorescence from different dyes that are used to identify the A, C, G, and T extension reactions. Contemporary or Pyrosequencer methods are based on detecting the activity of DNA polymerase (a DNA synthesizing enzyme) with another chemoluminescent enzyme. Essentially, the method allows sequencing of a single strand of DNA by synthesizing the complementary strand along it, one base pair at a time, and detecting which base was actually added at each step. |
| Website | |
| Platform | Univ_Georgia |
| Start Date | 2012-09-01 |
| End Date | 2014-10-31 |
| Description | Microbial 'omics studies |
Description from NSF award abstract:
Long-standing questions regarding the fate of dissolved organic carbon (DOC) in coastal oceans require a better understanding of the network that links bacterioplankton metabolism with carbon transformation. These questions address uncertainties about the composition of the bioreactive DOC components transformed in ocean margins, and the role of bacterial taxonomic and genetic composition in determining the fate of DOC.
This project will infuse a new type of data into coastal carbon cycle research based on high-resolution chemical analysis coupled with bacterial gene expression measures. It will extend DOC process studies down to the single-compound level and bacterial activity studies down to the single-gene level, and integrate this information into existing bioinformatic resources for biogeochemical and modeling applications.
The specific goals of this project are:
1) To reconstruct major components of the network linking DOC composition, DOC turnover, and bacterial heterotrophy in the coastal ocean (the composition of the DOC pool, the major bioreactive components, the bacterioplankton taxa mediating transformations, and the bacterial genes and pathways responsible).
2) To test hypothesized network links for selected DOC compounds using a simplified system that queries individual DOC compounds against a complex natural microbial community.
3) To test hypothesized network links for marine bacteria using a simplified system that queries a single generalist heterotrophic bacteria against a complex natural DOC pool.
4) To verify predicted DOC-gene linkages that are most informative about heterotrophic activities of bacterioplankton.
This research addresses fundamental questions on bacterial mediation of organic carbon fate in the ocean and atmosphere. As such, these investigations linking the chemical changes in dissolved organic carbon with patterns of gene expression in coastal bacterioplankton communities will be of interest to scientists across several disciplines.
---------------------------
Note: The project acronym, SIMCO, means "Sapelo Island Microbial Carbon Observatory".
| Funding Source | Award |
|---|---|
| NSF Division of Ocean Sciences (NSF OCE) |